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Spatial clusters of chronic preventable hospitalizations (ambulatory care sensitive conditions) and access to primary care.
Journal of Public Health 2019 April 13
BACKGROUND: Potentially preventable hospitalizations (PPHs) or ambulatory care sensitive conditions (ACSCs) represent hospitalizations that could be successfully managed in a primary care setting. Research from the USA and elsewhere on the role of primary care provider (PCP) access as a PPH driver has been conflicting. We investigated the role of PCP access in the creation of areas with persistently significant high rates of PPHs over time or PPH hotspots/spatial clusters.
METHODS: Using a detailed dataset of PCPs and a dataset of 106 334 chronic PPH hospitalizations from South Western Sydney, Australia, we identified hotspots of chronic PPHs. We contrasted how hotspot PPHs were different from other PPHs on a range of factors including PCP access.
RESULTS AND CONCLUSIONS: Six spatially contiguous areas comprising of eight postcodes were identified as hotspots with risks ranging from 1.6 to 2.9. The hotspots were found to be more disadvantaged and had better PCP access than other areas. Socioeconomic disadvantage explained the most variation (8%) in clustering while PCP access explained only a small fraction though using detailed PCP access measures helped. Nevertheless a large proportion of the variation remained unexplained (86.5%) underscoring the importance of individual level behaviours and other factors in driving chronic PPH clustering.
METHODS: Using a detailed dataset of PCPs and a dataset of 106 334 chronic PPH hospitalizations from South Western Sydney, Australia, we identified hotspots of chronic PPHs. We contrasted how hotspot PPHs were different from other PPHs on a range of factors including PCP access.
RESULTS AND CONCLUSIONS: Six spatially contiguous areas comprising of eight postcodes were identified as hotspots with risks ranging from 1.6 to 2.9. The hotspots were found to be more disadvantaged and had better PCP access than other areas. Socioeconomic disadvantage explained the most variation (8%) in clustering while PCP access explained only a small fraction though using detailed PCP access measures helped. Nevertheless a large proportion of the variation remained unexplained (86.5%) underscoring the importance of individual level behaviours and other factors in driving chronic PPH clustering.
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